Medical Research Agent Skills is a library of agent instructions for medical and biomedical research, covering evidence analysis, study protocol design, data analysis, and academic writing. Researchers use it to guide compatible coding agents through common scientific workflows. The catalogue contains many of the library's skills and commands.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aipoch/medical-research-skills --skill tumor-immune-infiltration-diagnostic-ml-research-plannergit clone --depth 1 https://github.com/aipoch/medical-research-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aipoch/medical-research-skills/tumor-immune-infiltration-diagnostic-ml-research-planner)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/tumor-immune-infiltration-diagnostic-ml-research-planner"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/tumor-immune-infiltration-diagnostic-ml-research-planner/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/tumor-immune-infiltration-diagnostic-ml-research-planner"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/tumor-immune-infiltration-diagnostic-ml-research-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00193 | $0.03930 |
| Opus 5 | $0.00097 | $0.01965 |
| Sonnet 5 | $0.00039 | $0.00786 |
| Haiku 4.5 | $0.00019 | $0.00393 |
Grade A, and why
tumor-immune-infiltration-diagnostic-ml-research-planner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tumor Immune-Infiltration Diagnostic ML Research Planner
You are an expert tumor immune-context bulk-transcriptome biomedical research planner.
Task: Generate a complete, structured research design — not a literature summary, not a tool list. A real, executable study plan with four workload options and a recommended primary path.
This skill is for tumor diagnostic biomarker / immune-linked machine-learning papers built around bulk expression datasets and clinically interpretable endpoints. Typical article logic includes: tumor vs control differential expression, immune infiltration estimation, immune-cell-associated module or correlation analysis, candidate compression, multi-algorithm feature selection, diagnostic classifier or nomogram construction, clinical association, optional survival extension, and optional tissue / protein / portal validation.
Input Validation
Valid input: [cancer type] + [immune-linked diagnostic direction OR biomarker direction OR ML diagnostic direction]
Optional additions: public-data-only, no wet lab, one final lead gene, specific immune cell focus, preferred config level, target journal tier, whether prognosis should be included.
Examples:
- "DLBCL. Need an M2-macrophage-related diagnostic biomarker study with ML + nomogram."
- "LUAD immune-infiltration diagnostic paper using bulk transcriptome only."
- "HCC. Want immune-cell-linked biomarkers, diagnostic model, and optional survival extension."
- "CRC. Public data only. Need Standard and Advanced."
Out-of-scope — respond with the redirect below and stop:
- Clinical trial protocols, dosing, prescribing, patient-specific treatment recommendations
- Pure scRNA-only, MR-only, GWAS-only, or radiomics-only studies with no bulk-transcriptome backbone
- Wet-lab-only studies with no computational planning framework
- Non-biomedical / off-topic requests
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- eval_report_tumor-immune-infiltration-diagnostic-ml-research-planner_result.json 13 KB
- references/analysis-modules.md 3.3 KB
- references/figure-deliverable-plan.md 1.9 KB
- references/literature-retrieval-and-citation.md 2.2 KB
- references/method-library.md 1.8 KB
- references/study-patterns.md 3.6 KB
- references/validation-evidence-hierarchy.md 2.3 KB
- references/workflow-step-template.md 1.8 KB
- references/workload-configurations.md 3.0 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 265 lines · 193 tokens per session scan A c2a379c2e13c
tumor-immune-infiltration-diagnostic-ml-research-planner is a skill published in the GitHub repository aipoch/medical-research-skills (1,869 stars, last pushed today), licensed MIT. It adds 193 tokens to every session and 3,930 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
statistical-modeling
Statistical modeling and machine learning for biomarker discovery, survival analysis, classification, regression, and model interpretation.
bulk-transcriptomics
Bulk RNA-seq and microarray differential expression analysis including method selection, batch correction, and complex experimental designs.
chromatin-regulation
Chromatin regulation analysis from called peaks and count matrices — differential binding, signal summarisation, peak annotation, and scATAC-seq.
spatial-omics
Spatial transcriptomics and spatial proteomics analysis covering technology-specific workflows, spatial statistics, deconvolution, and niche analysis.
atac-seq-bam-read-alignment-processing
Use when when you have aligned ATAC-seq BAM files and need to quantify Tn5 transposase insertion patterns around specific genomic coordinates (motif sites, peaks, regulatory regions) to detect transcription factor occupancy footprints or compare chromatin accessibility between bound and unbound.
bedgraph-file-format-manipulation
Use when you have aligned ChIP-Seq reads (in BED or BEDPE format) and need to convert them into quantitative genome-wide signal tracks (coverage, p-value, or q-value scores) for downstream statistical comparison or peak detection.